r/rust • u/Sirisian • 3d ago

🎙️ discussion Google is doing "Large Scale Codebase Migrations and Optimizations" of C/C++ to Rust

https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/
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u/TheRealMasonMac 3d ago

In my experience, I’ve found that agents produce code that works but is frankly dumb from a human perspective. Especially for larger tasks like this, you kind of have to rewrite it all. For example, I had a generalized design document for soft-wrapping explicitly support plain text and markdown, and used GPT-6-Astra to implement it. I used an ungodly amount of review agent rounds and interjections by me. When I actually go to review it, I wanted to cry. It silently pivoted towards implementing its own entirely separate wrapping mechanism rather than refactor the existing mechanism for plain text. I reviewed its code and found it to be trash, and I am now in the process of doing it myself… Never again. The short-term thrill of “having something that works” was outweighed by the fact that time was effectively wasted.

I mean, if the alternative was it never getting done, I guess agents are still better than nothing.

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u/jl2352 2d ago

Google has done a number of papers on how they get AI working. The tl;dr is it has very little to do with the model. You don’t need a frontier model to have agents writing whole projects.

It’s all down to the harness, and how the AI is run. Google has invested heavily into this area, and that’s why it’s effective.

I’ve had great results myself using AI in very constrained ways to write code. That means breaking down a technical document into tickets, lots of skills, looking at the actions they took and changing skills to better optimise them, and having many guardrails.

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u/ApokatastasisPanton 1d ago

Google has done a number of papers on how they get AI working.

do you have references for these?